AI-assisted development has made building software feel more credible than ever — a small team can now stand up a working claims workflow or policy tool in hours. That first result is real. But a working first version is not the same as a production-ready core system, and the gap between those two things is where carriers and MGAs get into serious trouble. In this on-demand session, Tom LoMedico and Origami Risk Chief Product and Technology Officer Ryan Cantor dig into what it actually means for an insurance organization to build its own policy administration, billing, or claims system in 2026. They cover what AI genuinely cannot supply — domain expertise, bureau content, state filing patterns, 20 years of insurance data modeling — and why the organizations best positioned to use AI are the ones investing in governed systems of record, not custom infrastructure. Whether you’re fielding internal pressure to build, evaluating your technology stack, or trying to sharpen the questions you ask before a build proposal gains momentum, this session gives you a practical framework for making the decision clearly. What you’ll learn: Why the complexity of core insurance software lives in the domain logic, not the code — and what AI genuinely cannot supply. Why build proposals for carriers and MGAs consistently undercount the true total cost of ownership. How key-person risk in a homegrown system becomes an existential liability disguised as an asset. What compliance and regulatory examination readiness actually require from a core insurance system — and the cost of discovering gaps after the fact. Why a modern vendor platform is the AI-ready foundation, not the conservative alternative to innovation.